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Modeling self-adaptative IoT architectures
1. 1
Iván Alfonso1,2, Kelly Garcés1,
Harold Castro1, Jordi Cabot2,3
Modeling self-adaptative
IoT architectures
1 University of the Andes, Bogotá, Colombia
2 Open University of Catalonia, Barcelona, Spain
3 ICREA, Barcelona, Spain
October 2021
2. Internet of Things 2
There will be 5.3 billion
internet users in 2023
(Cisco Annual Internet
Report)
3. Cloud
IoT Architecture 3
Network
device
Network
device
Network
device
Cloud
Device Layer
Collecting data
Sensors and actuators
Cloud Layer
Data processing and analysis
Business logic
Data storage
Data centers
Network
device
Network
device
Network
device
Cloud
Fog
node
Fog
node
Cloud Layer
Big data processing
Business logic
Data warehousing
Fog Layer
Local network
Local IoT analytics
Local storage
Edge Layer
Real time data processing
Micro sata storage
Low latency
Device Layer
Collecting data
Sensors and actuators
Cloud-based Multi-layer
4. Dynamic IoT Systems
• Unstable signal strength
• Latency growth
• Software failures
4
• Auto-scaling
• Offloading tasks
• Redeployment services
Unexpected events at runtime Adaptations
10. Domain Specific Language (DSL) 10
{
__;
_____;
}
DSL
• Modeling (four layers) of an IoT system,
including IoT devices, edge, fog, and cloud
nodes.
• Modeling the deployment of container-based
applications.
• A specific sublanguage to express adaptation
32. Conclusion
& Future
Work
• DSL for modeling IoT systems
• Multi-layered architectures
• Self-adaptation rules
• First steps towards a self-adaptive IoT
system architecture
• Extend the DSL to express more complex
adaptation strategies
• Extend the code generator to cover the dynamic
aspects
• Validate the DSL in the mining industry
FUTURE
33. 33
Iván Alfonso1,2, Kelly Garcés1,
Harold Castro1, Jordi Cabot2,3
Thanks
1 University of the Andes, Bogotá, Colombia
2 Open University of Catalonia, Barcelona, Spain
3 ICREA, Barcelona, Spain
October 2021
35. Future Approach 35
Developer
IoT System
IoT architecture
(YAML)
Adaptation rules
(PromQL)
DESIGN TIME
Prometheus
RUN TIME
Orchestrator
Model
Code
Generator
Adapter
Alert
Manager
Notas do Editor
The Offloading action consists in migrating a container from a source node to a destination node.
The Scaling action involves deploying replicas of an application (the number of replicas to be deployed is defined by the instances attribute).
The Redeployment action consists in stopping and redeploying a container running on a node.
And the OperateActuator action is to control the actuators of the system (e.g. to activate or deactivate an alarm).
Our DSL is implemented using MPS, an open-source language workbench developed by Jetbrains. In addition, we have developed a proof-of-concept of a code generator.
K3S is a Kubernetes distribution built for IoT and edge computing. We chose this orchestrator mainly because of its light weight, and we also chose it because it supports ARM processors.